Numerical health assessment of surface wear in mechanical contacts PhD

The research in this doctoral opportunity will numerically assess single/multiple point wear in mechanical contacts and its relation with airborne friction noise.

Friction noise and wear phenomena are inevitable in machine components even working in normal operational conditions. Surface degradation, at the mechanical contacts due to wear, has an impact on the noise emitted because of the rapid release of energy from localized sources within a material. Severity of surface degradation can change the noise spectrum, and hence an analysis of emitted noise can lead to the possible health diagnosis of machine components.

Researchers have shown the empirical trend modelling between noise signals and the wear in terms of accumulated signal energy and changes in spectrum amplitude. However, due to complexities in wear tribo-mechanics, it is still a challenge to numerically generate friction noise even for a single mechanical contact which is under degradation due to wear phenomenon.

In this research, numerical modelling will be performed for assessing the relationship between the friction noise and wear in mechanical contacts. Asperities of contacts will be tangentially loaded in such a manner that one of the contact asperity will be assumed as static and the other will create sliding effect for the wear. The materials selection will also allow to assume that one of the material asperity will be worn out while other will be responsible for the generation of the compression wave in the air medium. Later, this compression wave will be used to generate the friction noise, which will further be used to investigate the wear in contact.

Entry Requirements:
- A minimum of a 2:1 first degree in a relevant discipline/subject area (e.g. aerospace, automotive, mechanical, and manufacturing) with a minimum 60% mark in the Project element or equivalent with a minimum 60% overall module average
- The potential to engage in innovative research and to complete the PhD within a three-year period of study
- A minimum of English language proficiency (IELTS overall minimum score of 6.5)
- Excellent analytical, reporting and communication skills
- Self-motivated, independent and team player
- Genuine enthusiasm for the subject and technology
- Willingness to publish research findings in international journals

Funding: Self-funded

Duration: 3 years

Eligibility: UK, EU, Rest of world

Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network. This Network brings together both research students and staff, providing a platform for researchers to share ideas, identify opportunities for collaboration and create smaller communities of practice.

An important part of the research journey is developing key skills through the Doctoral Researchers' Core Development (DRCD) Programme, which comprises four 1-week units covering the key stages of the research journey. Workshops are held face to face, providing the opportunity to network and collaborate with peers.

Supervisors: Dr Muhammad Khan (Head of Center and Reader in Damage Mechanics) and Professor Andrew Starr (Professor of Maintenance Systems).